Cascade: A Platform for Delay-Sensitive Edge Intelligence

TL;DR

Cascade is a new AI/ML platform designed for delay-sensitive edge applications, significantly reducing latency while maintaining high throughput through innovative data management and computation strategies.

Contribution

It introduces a legacy-friendly storage layer and a fast path for data-computation colocation, optimizing AI/ML hosting for low-latency edge intelligence.

Findings

Reduces latency by orders of magnitude

Maintains high throughput

Enhances responsiveness in edge AI applications

Abstract

Interactive intelligent computing applications are increasingly prevalent, creating a need for AI/ML platforms optimized to reduce per-event latency while maintaining high throughput and efficient resource management. Yet many intelligent applications run on AI/ML platforms that optimize for high throughput even at the cost of high tail-latency. Cascade is a new AI/ML hosting platform intended to untangle this puzzle. Innovations include a legacy-friendly storage layer that moves data with minimal copying and a "fast path" that collocates data and computation to maximize responsiveness. Our evaluation shows that Cascade reduces latency by orders of magnitude with no loss of throughput.